1. 1 Gesture recognition Using HMMs and size functions

2. 2 Approach Combination of HMMs (for dynamics) and size functions (for pose representation)

3. 3 Size functions Topological representation of contours

4. 4 Measuring functions Functions on the contour to which the size function is computed real image measuring function family of lines

5. 5 Feature extraction 1 An edge map is extracted from the image real imageedge map … and …

6. 6 Feature extraction 2 a family of measuring functions is chosen … the szfc are computed, and their means form the feature vector

7. 7 Hidden Markov models Finite-state model of gestures as sequences of a small number of poses

8. 8 Four-state HMM Gesture dynamics -> transition matrix A Object poses -> state-output matrix C

9. 9 EM algorithm feature matrices: collection of feature vectors along time EM A,C learning the models parameters through EM two instances of the same gesture

10. 10 EM algorithm -> learning the models parameters Learning algorithm

11. 11 Gesture classification … HMM 1 HMM 2 HMM n the new sequence is fed to the learnt gestures models they produce a likelihood the most likely model is chosen (if above a threshold)